While the investment objective stated in a fund’s prospectus may or may not reflect how the fund actually invests, the Morningstar category is assigned based on the underlying securities in each portfolio.

Morningstar categories help investors and investment professionals make meaningful comparisons between funds. The categories make it easier to build well-diversified portfolios, assess potential risk, and identify top-performing funds. We place funds in a given category based on their portfolio statistics and compositions over the past three years.

Categories are the foundation of a system that rates and ranks each fund against its “peers.” While this methodology simplifies comparisons by narrowing the scope, it has multiple drawbacks:

Even with restraint, it tends to proliferate categories (see above)

It lowers the bar by using an average fund performance in a given category (see a broader explanation in our FAQ)

If the category assignment is subsequently changed as a result of a review, prior ratings have to be largely discarded because of a different set of peer funds

Some funds may not lend themselves to an easy categorization because of an eclectic or frequently fluctuating investment strategy (not to be confused with a stated objective).

The article demonstrates the last of the above flaws by describing problems with an accurate classification of the Osterweis (OSTFX) and other funds. The Osterweis Fund is currently assigned to the domestic Mid-Cap Blend category, even though its holdings span a broad range of market capitalization and include foreign stocks.

This is where Alpholio™’s approach comes to the rescue. Our methodology addresses all of the above problems by comparing each fund against a custom reference portfolio of ETFs. The reference portfolio is constructed without any preconception of a fund’s category (although we use a small set of “categories” to narrow down the fund search). Moreover, unlike a static category assignment, the reference portfolio is dynamic in terms of both the membership and weights of its members. This adapts the reference to any changes in the fund’s investment profile and makes the performance assessment (i.e. RealAlpha™) portable across categories.

In addition, our analysis does not rely on a periodic disclosure of fund holdings, which itself suffers from numerous problems. It also avoids issues related to the changing classification of individual holdings in a fund, which is inherent in a “bottom-up” analysis (for example, consider the stock of Apple Inc., which could be classified as growth or value depending on one’s point of view).

To demonstrate, let’s take a closer look at the Osterweis Fund. Here are the weights of ETFs in its reference portfolio since early 2005:

After an equivalent position in the iShares 1-3 Year Treasury Bond ETF (SHY; average weight of 24.6%) representing short-term investments, the fund’s equivalent position with the second highest average weight was in the iShares Core S&P Mid-Cap ETF (IJH; 13.6%). The latter explains why Morningstar classified the fund into the Mid-Cap Blend category.

As in the case of OSTFX, the ETF weights for FLPSX significantly fluctuated over the nine-year analysis period. For example, the equivalent position in VO was as high as 57.2% and as low as 0%, while JKJ oscillated between 44.8% and 2.2%. Therefore, a fixed classification of this fund into the Mid-Blend category since 2005 is dubious.

In conclusion, Alpholio™’s innovative approach alleviates the disadvantages of a simplified categorizing of mutual funds. The traditional classification methodology will continue to suffer from its inherent tradeoff among the number, accuracy and persistence of categories assigned to mutual funds.